BUG: Groupby summing over infinity values yields NaN

[FabianHofmann]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
import numpy as np

ser = pd.Series([np.inf, np.inf])

ser.sum() == np.inf # True, all fine



grouper = pd.Series(['a', 'a'])

ser.groupby(grouper).sum() # yields NaN, expected infinity

ser.groupby(grouper).agg("sum") # yields NaN, expected infinity

Issue Description

When performing a groupby operation with a sum over values which include infinity values, the result yield NaN values instead of infinity.

Expected Behavior

Expected infinity as a result (as in accord to directly summing over multiple infinity values)

Installed Versions

INSTALLED VERSIONS

commit : 0f43794
python : 3.11.3.final.0
python-bits : 64
OS : Linux
OS-release : 6.3.3-060303-generic
Version : #202305171336 SMP PREEMPT_DYNAMIC Wed May 17 13:45:19 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.3
numpy : 1.24.3
pytz : 2022.7
dateutil : 2.8.2
setuptools : 66.0.0
pip : 23.0.1
Cython : 0.29.33
pytest : 7.3.1
hypothesis : None
sphinx : 5.0.2
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.13.2
pandas_datareader: None
bs4 : 4.12.2
bottleneck : 1.3.5
brotli :
fastparquet : None
fsspec : 2023.4.0
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.1
snappy : None
sqlalchemy : None
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.6.1.dev398+ge739df7d
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : 2023.3
qtpy : 2.2.0
pyqt5 : None

[lithomas1]

This works on main for me.

>>> import pandas as pd
>>> import numpy as np
>>> 
>>> ser = pd.Series([np.inf, np.inf])
>>> 
>>> ser.sum() == np.inf # True, all fine
True
>>> 
>>> 
>>> 
>>> grouper = pd.Series(['a', 'a'])
>>> 
>>> ser.groupby(grouper).sum() # yields NaN, expected infinity
a    inf
dtype: float64
>>> 
>>> ser.groupby(grouper).agg("sum") # yields NaN, expected infinity
a    inf
dtype: float64

[lithomas1]

2.1 will be out in ~ a months time, maybe you can wait until then?

[rhshadrach]

Closing as a duplicate of #53606 and #43292